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Routes Queries Across Models and Humans

Gungun Pandey turned a Rubric eval platform into a decision-model lab and added Jev to compare structured decisions with chat LLMs. In a routing pipeline, Jev directs queries to RAG, a small LLM, a big LLM, or a human.

View on X cost2× lower cost/1Ktime2.3× lower p50 latency (1.02s vs 2.39s)
Gungun Pandey@gungunsegfault𝕏
I turned my Rubric eval platform into a small decision-model lab. Added Jev and started comparing it with chat LLMs on the same structured decisions. First run: Jev hit 100% accuracy, matching GPT-4o-mini, while showing 2.3× lower p50 latency (1.02s vs 2.39s) and 2× lower cost/1K. Then I put Jev into an actual routing pipeline instead of testing it in isolation, query → Jev → RAG / small LLM / big LLM / human, instead of throwing every query at the same model. Interesting part: the handwritten rules router got 100% route accuracy with 0 wrong routes, while Jev got 93.8% with 1 wrong route. Jev
Sep 23, 2026X postsView on X
In the first evaluation, Jev matched GPT-4o-mini at 100% accuracy. In the routing test, Jev achieved 93.8% route accuracy with one wrong route, while the handwritten-rules router achieved 100% with none.

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